A performance comparison of hand motion EMG classification

Sungtae Shin, Reza Tafreshi, Reza Langari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

Powered prosthesis is of considerable value to amputees to enable them to perform their daily-life activities with convenience. One of applicable control signals for controlling a powered prosthesis is the myoelectric signal. A number of commercial products have been developed that utilize myoelectric control for powered prostheses; however, the functionality of these devices is still insufficient to satisfy the needs of amputees. For the purpose of a comparison, several electromyogram classification methods have been studied in this paper. The performance criteria included not only classification accuracy, but also repeatability and robustness of the classifier, training time for online training performance, and computational time for real-time operation were evaluated with seven classification algorithms. The study included five different feature sets with time-domain feature values and autoregressive model coefficients. In summary, the quadratic discriminant analysis showed a remarkable performance in terms of high classification accuracy, high robustness, and low computational time of training and classification from the experiment results.

Original languageEnglish
Title of host publication2014 Middle East Conference on Biomedical Engineering, MECBME 2014
PublisherIEEE Computer Society
Pages353-356
Number of pages4
ISBN (Print)9781479947997
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014 - Doha, Qatar
Duration: 17 Feb 201420 Feb 2014

Publication series

NameMiddle East Conference on Biomedical Engineering, MECBME
ISSN (Print)2165-4247
ISSN (Electronic)2165-4255

Other

Other2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014
CountryQatar
CityDoha
Period17/2/1420/2/14

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ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Shin, S., Tafreshi, R., & Langari, R. (2014). A performance comparison of hand motion EMG classification. In 2014 Middle East Conference on Biomedical Engineering, MECBME 2014 (pp. 353-356). [6783276] (Middle East Conference on Biomedical Engineering, MECBME). IEEE Computer Society. https://doi.org/10.1109/MECBME.2014.6783276